The Internet of Things generates vast amounts of data that are often useful not only to the organization owning or operating the IoT devices generating the data, but also to other organizations. For example, power consumption as measured by one utility company may be of interest to other utility companies, and weather data acquired by a network of meteorology stations may be useful to both utility companies as well as to individuals retrieving local weather data via smartphones. Accordingly, there may be incentives for sharing data between IoT networks acting as data producers and/or data consumers, respectively. Data acquired by one IoT network may, for instance, be streamed to others for an agreed-upon price. To support their use cases, data consumers combine, in many situations, data streams from multiple data producers, but often use only part of the data in the individual data streams. This results in the unnecessary use of bandwidth to transmit data ultimately filtered out by the consumer system, and tends to require significant manual effort to filter and aggregate data across data streams with little to no knowledge of the data's proven quality.